Multiclass learning at one-class complexity

We show in this paper the multiclass classification problem can be implemented in the maximum margin framework with the complexity of one binary Support Vector Machine. We show reducing the complexity does not involve diminishing performance but in some cases this approach can improve the classification accuracy. The multiclass classification is realized in the framework where the output labels are vector valued.